Social Network Analysis: Modularity Measure

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Related lectures (30)

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Link-based Ranking: Fundamentals and Algorithms

Covers the fundamentals and algorithms of link-based ranking, including anchor text indexing, PageRank, HITS, and practical implementations.

Graph Theory and Network Flows

Introduces graph theory, network flows, and flow conservation laws with practical examples and theorems.

Fixed Points in Graph Theory

Focuses on fixed points in graph theory and their implications in algorithms and analysis.

Algorithmic Paradigms for Dynamic Graph Problems

Covers algorithmic paradigms for dynamic graph problems, including dynamic connectivity, expander decomposition, and local clustering, breaking barriers in k-vertex connectivity problems.

Social and Information Networks: Ranking

Explores the significance of ranking in networks, emphasizing algorithms like PageRank and HITS for web page ranking.

Handling Network Data

Covers handling network data, types of graphs, centrality measures, and properties of real-world networks.

Epidemic Spreading Models

Covers classical models of epidemic spreading and dynamics on networks with examples.

Social Network Analysis: Friendship Relations

Introduces social network analysis through Python code modeling friendship relations.

Graph Algorithms II: Traversal and Paths

Explores graph traversal methods, spanning trees, and shortest paths using BFS and DFS.

Stochastic Blockmodel Estimation

Explores Stochastic Blockmodel estimation, spectral clustering, network modularity, Laplacian matrix, and k-means clustering.